Engineering trust-awareness and self-adaptability in services and systems

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Abstract

The Future Internet (FI) comprises scenarios where many heterogeneous and dynamic entities must interact to provide services (e.g., sensors, mobile devices and information systems in smart city scenarios). The dynamic conditions under which FI applications must execute call for self-adaptive software to cope with unforeseeable changes in the application environment. Models@run.time is a promising modeldriven approach that supports the runtime adaptation of distributed, heterogeneous systems. Yet frameworks that accommodate this paradigm have limited support to address security concerns, hindering their usage in real scenarios. We address this challenge by enhancing models@ run.time with the concepts of trust and reputation. Trust improves decision-making processes under risk and uncertainty and constitutes a distributed and flexible mechanism that does not entail heavyweight administration. This chapter introduces a trust and reputation framework that is integrated into a distributed component model that implements the models@run.time paradigm, thus allowing software components to include trust in their reasoning process. The framework is illustrated in a smart grid scenario.

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APA

Moyano, F., Fernandez-Gago, C., Baudry, B., & Lopez, J. (2014). Engineering trust-awareness and self-adaptability in services and systems. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8431, 180–209. https://doi.org/10.1007/978-3-319-07452-8_8

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